A knowledge identification framework for the engineering of ontologies in system composition processes

Mitchell G. Gillespie, Hlomani Hlomani, Daniel Kotowski, Deborah A. Stacey

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Citations (Scopus)

Abstract

Recent research has been focused on the creation of intelligent compositional systems that utilize ontologies as a knowledge base to facilitate the composition of new systems/workflows. Within this ontology-driven compositional systems field, experts have created knowledge representation models to satisfy requirements of their own domain rather than considering a general perspective. This paper proposes a knowledge identification framework to facilitate collaborative decision-making during knowledge requirement gathering to assist in the capture, merging, and mapping within an ontology engineering methodology. Five categories of knowledge (and a mapping of their relationships) are recognized as knowledge elements that should at least be considered in any representation model. A differentiation of syntactic and semantic knowledge, and a depiction of external influences on the composition process is also included. The paper concludes that while the presented framework does not guarantee an optimal ontological model, it does assist with the knowledge identification process for single or multiple stakeholders in ontology engineering for compositional systems.

Original languageEnglish
Title of host publicationProceedings of the 2011 IEEE International Conference on Information Reuse and Integration, IRI 2011
Pages77-82
Number of pages6
DOIs
Publication statusPublished - 2011
Event12th IEEE International Conference on Information Reuse and Integration, IRI 2011 - Las Vegas, NV, United States
Duration: Aug 3 2011Aug 5 2011

Other

Other12th IEEE International Conference on Information Reuse and Integration, IRI 2011
CountryUnited States
CityLas Vegas, NV
Period8/3/118/5/11

Fingerprint

Ontology
Chemical analysis
Knowledge representation
Intelligent systems
Syntactics
Merging
Identification (control systems)
Decision making
Semantics

All Science Journal Classification (ASJC) codes

  • Information Systems
  • Information Systems and Management

Cite this

Gillespie, M. G., Hlomani, H., Kotowski, D., & Stacey, D. A. (2011). A knowledge identification framework for the engineering of ontologies in system composition processes. In Proceedings of the 2011 IEEE International Conference on Information Reuse and Integration, IRI 2011 (pp. 77-82). [6009524] https://doi.org/10.1109/IRI.2011.6009524
Gillespie, Mitchell G. ; Hlomani, Hlomani ; Kotowski, Daniel ; Stacey, Deborah A. / A knowledge identification framework for the engineering of ontologies in system composition processes. Proceedings of the 2011 IEEE International Conference on Information Reuse and Integration, IRI 2011. 2011. pp. 77-82
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Gillespie, MG, Hlomani, H, Kotowski, D & Stacey, DA 2011, A knowledge identification framework for the engineering of ontologies in system composition processes. in Proceedings of the 2011 IEEE International Conference on Information Reuse and Integration, IRI 2011., 6009524, pp. 77-82, 12th IEEE International Conference on Information Reuse and Integration, IRI 2011, Las Vegas, NV, United States, 8/3/11. https://doi.org/10.1109/IRI.2011.6009524

A knowledge identification framework for the engineering of ontologies in system composition processes. / Gillespie, Mitchell G.; Hlomani, Hlomani; Kotowski, Daniel; Stacey, Deborah A.

Proceedings of the 2011 IEEE International Conference on Information Reuse and Integration, IRI 2011. 2011. p. 77-82 6009524.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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Gillespie MG, Hlomani H, Kotowski D, Stacey DA. A knowledge identification framework for the engineering of ontologies in system composition processes. In Proceedings of the 2011 IEEE International Conference on Information Reuse and Integration, IRI 2011. 2011. p. 77-82. 6009524 https://doi.org/10.1109/IRI.2011.6009524